Laboratory for Artificial Intelligence Research & Engineering (LAIRE) Housed in Electrical Engineering & Computer Science Laboratory for Artificial Intelligence Research & Engineering (LAIRE) Housed in Electrical Engineering & Computer Science Breadcrumb research west point werx robotics research center laboratory for artificial intelligence research engineering About the LAIRE The Laboratory for Artificial Intelligence Research & Engineering (LAIRE) was established in 2025 at the United States Military Academy at West Point. Housed within the Robotics Research Center, LAIRE conducts fundamental and applied research and engineering in artificial intelligence (AI), including mathematics, information theory, decision science and advanced computing, needed to design and develop computationally intelligent robotics and autonomous Command, Control, Computing, Communications, Cyber, Intelligence, Surveillance, Reconnaissance and Targeting (C5ISRT) systems to solve U.S. Army and Department of Defense problems (DoD) with a specific focus on enabling rapid, effective decision-making in network centric environments. Research Concentration Areas Methods for multi-modal, multi-scale, heterogeneous data/information integrationMathematics for AI uncertainty quantification needed for trusted decision-makingModeling hierarchical, contextual knowledge for complex multi-modal scene understandingNeuro-symbolic architectures for representation, learning, reasoning, and inferenceBiology-inspired metacognitive AI paradigms, such as hyperdimensional computingApproaches to ensure the security, robustness, and resiliency of AI with provable guaranteesSelf-improving adaptation methods for anti-fragile AI in edge computing environments Recent Publications Yeung, C., Zou, Z., Bastian, N. & Imani, M. (2025). Cognitive Map Formation Under Uncertainty via Local Prediction Learning. Intelligent Systems with Applications, 27(200551), pp. 1-11.Ravari, A., Ghoreishi, S., Lan, T., Bastian, N. & Imani, M. (2025). Hybrid Modeling of Heterogeneous Human Teams for Collaborative Decision Processes. Proceedings of Machine Learning Research (7th Annual Conference on Learning for Dynamics & Control), 283, pp. 830-843.Cybenko, G., Lintilhac, P., Ackerman, J. & Bastian, N. (2025). Quantifying Adversarial Risk of Multimodal Foundation Models for Military Applications. Proceedings of the 2025 SPIE DCS Conference on Assurance and Security for AI-enabled Systems (134760J), pp. 134760J-1 – 134760J-18, SPIE Defense + Commercial Sensing (Volume: 13476).Beggs, J., Coffey, S., Murphy, J. & Bastian, N. (2025). Resource-Efficient, Self-Adaptive Neuro-Symbolic Artificial Intelligence for the Internet of Battlefield Things. Proceedings of the 2025 SPIE DCS Conference on Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications VII (1347308), pp. 1347308-1 – 1347308-12, SPIE Defense + Commercial Sensing (Volume: 13473).Shakarian, P., Simari, G. & Bastian, N. (2025). Probabilistic Foundations for Metacognition via Hybrid-AI. Proceedings of the 2025 AAAI Spring Symposium on Machine Learning and Knowledge Engineering for Trustworthy Multimodal and Generative AI, pp. 1-5.Yun, S., Masukawa, R., Chung, W., Na, M., Bastian, N. & Imani, M. (2025). Continuous CNN-based Anomaly Detection on Edge using Efficient Adaptive Knowledge Graph Learning. Proceedings of the 2025 IEEE/ACM Design, Automation and Test in Europe Conference, pp. 1-8. LAIRE Resources Lab publications EECS Resources Electrical Engineering & Computer ScienceRobotics Research Center